The Past as a Stochastic Process

TL;DR

This paper introduces a stochastic process framework for analyzing large historical datasets, enabling the detection of patterns, causal actors, and comparisons across cases, complementing traditional historical narratives.

Contribution

It presents a novel application of stochastic processes to history and archaeology, providing a structured analytical approach for complex historical data.

Findings

Identifies patterns in large historical datasets.

Detects relevant causal actors, endogenous and exogenous.

Enables comparison between different historical cases.

Abstract

Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted to identify patterns and categorize historical actors and influences with some success. A stochastic process framework provides a structured approach for the analysis of large historical datasets that allows for detection of sometimes surprising patterns, identification of relevant causal actors both endogenous and exogenous to the process, and comparison between different historical cases. The combination of data, analytical tools and the organizing theoretical framework of stochastic processes complements traditional narrative approaches in history and archaeology.